Three economists (Tobias Preis of Warwick Business School in the U.K., Helen Susannah  Moat of University College London, and H. Eugene Stanley of Boston University) have published a paper that said Google Trends data was useful in predicting daily price moves in the Dow Jones industrial average, which consists of 30 stocks.

They found that an uptick in Google searches on finance terms reliably predicted a fall in stock prices. Within those different financial terms, they found that “Debt” was the most reliable term for predicting market ups and downs. The researchers were able to increase their hypothetical portfolio by 326 percent by going long when “debt” searches dropped and shorting the market when “debt” searches rose.

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Big Data Gets Bigger: Now Google Trends Can Predict The Market
Yesterday three economists, (Tobias Preis of Warwick Business School in the U.K., Helen Susannah Moat of University College London, and H. Eugene Stanley of Boston University) published an eye-openin…

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